A variety of safety systems have been made available to date to provide improved safety, for example, in automobile sector.
Recent years have seen the commercialization of a target detection system designed to detect a target such as pedestrians or vehicles using a plurality of stereo cameras or other types of cameras.
The above target detection system calculates the positional deviation (disparity) of the same target in a plurality of images captured at the same time by a plurality of cameras (imaging devices) based, for example, on template matching and calculates the position of the target in a real space based on the disparity and a known conversion formula, thus detecting the target.
A stereo camera-based target detection system such as the one described above designed to recognize a target by calculating distance to the target using a pair of images captured by a plurality of cameras (imaging devices) is applicable not only to the above vehicle safety system but also to a monitoring system adapted to detect entry of an intruder and anomalies.
A stereo camera-based target detection system applied to the above safety system and monitoring system captures images of a target with a plurality of cameras arranged with a given spacing provided therebetween and applies a triangulation technique to the pair of images captured by the plurality of cameras, thus calculating distance to the target.
More specifically, the target detection system includes, in general, at least two imaging devices (cameras) and a stereo image processing LSI (Large Scale Integration). The stereo image processing LSI applies a triangulation process to at least two captured images output from these imaging devices. The stereo image processing LSI performs arithmetic operations to superimpose pixel information included in the pair of images captured by the plurality of cameras and calculates the positional deviation (disparity) between the matching positions of the two captured images, thus performing the triangulation process. It should be noted that, in such a target detection system, each of the imaging devices must be adjusted to eliminate deviations in optical, signal and other characteristics between the imaging devices, and the distance between the imaging devices must be found precisely in advance, in order to ensure that there is no deviation other than disparity in the pair of images captured by the plurality of cameras.
FIG. 9 describes the principle behind the stereo camera-based target detection system. In FIG. 9, σ is the disparity (positional deviation between the matching positions of the pair of captured images), Z is the distance to the target to be measured, f is the focal distance of the imaging device, and b is the base line length (distance between the imaging devices). Formula (1) shown below holds between these parameters.[Formula 1]Z=b·f/σ  (1)
Incidentally, a stereo camera-based target detection system has a problem in that because the longer the distance to the target to be measured, the smaller the disparity σ, decline in the capability to calculate the disparity σ results in lower accuracy in calculating the distance to the target. Further, when located far away, the target becomes smaller in the captured image. Therefore, dirt or raindrops adhering to the lens of one of the cameras or the lenses of both thereof make it difficult to recognize that target, thus resulting in even lower accuracy in calculating the distance to the target.
In order to solve such a problem, Patent Document 1 discloses a technology for merging stereo camera and monocular camera technologies to complement the drawbacks of the two technologies.
The three-dimensional coordinate acquisition device disclosed in Patent Document 1 calculates three-dimensional coordinates of a target from images captured by monocular and stereo cameras so as to simply switch between the two calculation results or combining the two results. Further, when combining the two calculation results, this device changes the weights of the results in accordance with the distances from the cameras to the target, the vehicle speed, the number of flows, and the accuracy.